Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Paul Manason Sahala Simanjuntak
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sistem Pakar Diagnosa Penyakit Gigi dan Mulut Menggunakan Metode Naive Bayes - Weighted Product Paul Manason Sahala Simanjuntak; Edy Santoso; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (931.216 KB)

Abstract

Teeth and mouth are parts of the body that are often lacking in health. Dental and Mouth Disease is included in the list of 10 diseases that people often complain about. Dental disease itself is often considered trivial by the public, even though if it is not treated immediately it can cause heart disease and stroke. The uneven distribution of dental and oral experts has made it difficult for people to be able to get dental and oral health checks. Therefore, it is expected that with this system can help people especially those that are not reached by a dental expert to be able to find out the diagnosis of dental and oral diseases suffered and advice that can be given. In this system the method used in the diagnosis process is the naive bayes-weighted product method. Naive Bayes itself is applied to find the value of the probability of each symptom of a disease while the weighted product is applied to provide a conclusion on the diagnosis of dental and oral diseases by finding the value of the criteria s and alternative values ​​v. In this system there are 7 types of diseases and 21 dental and oral disease symptoms that can be recognized by the system. Accuracy testing results use a total of 30 test data and produce an accuracy rate of 93.3%.
Co-Authors Edy Santoso Tibyani Tibyani